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Deeksha Jampulu

@deekshajampulu

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Data Scientist with 7+ years of experience in AI/ML solutions.

United States

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What I'm looking for

I am looking for a role that challenges me with innovative AI projects and fosters collaboration in a dynamic team environment.

I am a seasoned Data Scientist with over 7 years of experience in developing and deploying scalable AI and machine learning solutions across various domains, including FinTech, Healthcare, and E-commerce. My expertise lies in model engineering and data-driven optimization, where I have successfully implemented real-time fraud detection systems and predictive models that have significantly improved operational efficiency and decision-making processes.

Throughout my career, I have honed my skills in Python, SQL, and R, utilizing advanced tools such as TensorFlow, Scikit-learn, and XGBoost to build end-to-end supervised and unsupervised learning systems. I am passionate about leveraging AI responsibly to solve complex problems, and I have a proven track record of collaborating with cross-functional teams to ensure that our models align with both technical and strategic business goals.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer

Current

Truist Bank

Jun 2022 - Present (3 years)

Led the development of an AI-driven fraud detection and financial intelligence system. Operationalized ML workflows using AWS SageMaker, GCP Vertex AI, and Azure ML Studio, enabling scalable training, deployment, and lifecycle tracking across environments.

Python SQL Pandas NumPy XGBoost TensorFlow BERT Apache Spark Databricks

Machine Learning Engineer

Quantum Health

Apr 2019 - Present (6 years 2 months)

Developed predictive models to identify high-risk patients with chronic conditions, enabling early interventions and reducing hospital readmissions. Built ETL pipelines using Pandas, NumPy, and SQL to clean, normalize, and structure data from EHRs, claims systems, and patient-reported outcomes.

Python SQL Pandas NumPy XGBoost TensorFlow Logistic Regression K Means

Data Scientist

Costco

Aug 2017 - Present (7 years 10 months)

Developed predictive models using Logistic Regression, Random Forest, and XGBoost to identify customers likely to churn, abandon carts, or convert into repeat buyers. Built user segmentation and recommendation pipelines using K-Means clustering and behavioral pattern analysis.

Python SQL Pandas NumPy XGBoost Logistic Regression Random Forest K Means TensorFlow

Education

Degrees, certifications, and relevant coursework

University of North Texas

Masters, Business Analytics

Studied advanced concepts in business analytics, focusing on data-driven decision-making. Gained expertise in statistical modeling, data mining, and predictive analytics relevant to business applications.